Several criteria from the optimal design literature are examined for use with item selection in multidimensional adaptive testing. In particular, it is examined what criteria are appropriate for adaptive testing in which all abilities are intentional, some should be considered as a nuisance, or the interest is in the testing of a composite of the abilities. Both the theoretical analyses and the studies of simulated data in this paper suggest that the criteria of A-optimality and D-optimality lead to the most accurate estimates when all abilities are intentional, with the former slightly outperforming the latter. The criterion of E-optimality showed occasional erratic behavior for this case of adaptive testing, and its use is not recommended...
Items with the highest discrimination parameter values in a logistic item response theory (IRT) mode...
Computerized adaptive tests (CATs) were originally developed to obtain an efficient estimate of the ...
The case of adaptive testing under a multidimensional response model with large numbers of constrain...
Several criteria from the optimal design literature are examined for use with item selection in mult...
The case of adaptive testing under a multidimensional logistic response model is addressed. An adapt...
The case of adaptive testing under a multidimensional logistic response model is addressed. An adapt...
A classification method is presented for adaptive classification testing with a multidimensional ite...
A classification method is presented for adaptive classification testing with a multidimensional ite...
Maximum likelihood and Bayesian procedures for item selection and scoring of multidi-mensional adapt...
In this study some alternative item selection criteria for adaptive testing are proposed. These crit...
adaptive testing, Fisher information matrix, multidimensional IRT, optimal design,
This computer simulation study was designed to comprehensively investigate how formative test design...
Adaptive testing under a multidimensional logistic response model is addressed. An algorithm is prop...
ABSTRACT. Item Response Theory is the psychometric model used for standardized tests such as the Gra...
Computerized adaptive tests (CATs) were originally developed to obtain an efficient estimate of the ...
Items with the highest discrimination parameter values in a logistic item response theory (IRT) mode...
Computerized adaptive tests (CATs) were originally developed to obtain an efficient estimate of the ...
The case of adaptive testing under a multidimensional response model with large numbers of constrain...
Several criteria from the optimal design literature are examined for use with item selection in mult...
The case of adaptive testing under a multidimensional logistic response model is addressed. An adapt...
The case of adaptive testing under a multidimensional logistic response model is addressed. An adapt...
A classification method is presented for adaptive classification testing with a multidimensional ite...
A classification method is presented for adaptive classification testing with a multidimensional ite...
Maximum likelihood and Bayesian procedures for item selection and scoring of multidi-mensional adapt...
In this study some alternative item selection criteria for adaptive testing are proposed. These crit...
adaptive testing, Fisher information matrix, multidimensional IRT, optimal design,
This computer simulation study was designed to comprehensively investigate how formative test design...
Adaptive testing under a multidimensional logistic response model is addressed. An algorithm is prop...
ABSTRACT. Item Response Theory is the psychometric model used for standardized tests such as the Gra...
Computerized adaptive tests (CATs) were originally developed to obtain an efficient estimate of the ...
Items with the highest discrimination parameter values in a logistic item response theory (IRT) mode...
Computerized adaptive tests (CATs) were originally developed to obtain an efficient estimate of the ...
The case of adaptive testing under a multidimensional response model with large numbers of constrain...